Mentor
German H. Alferez, Ph.D.
Date of Award
Spring 4-12-2024
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
First Advisor
German H. Alferez, Ph.D.
Second Advisor
Robert Ordonez, MSc.
Third Advisor
Brent Hamstra, Ph.D.
Abstract
Since the introduction of transformers, large language models have proven capable in many natural language processing fields. However, existing systems still face challenges in generating high-quality extractive questions. Base models and public chatbots fall short if the question source or quantity are critical. Our contribution is a question and answer generator for generating comprehensive, extractive questions and answers. This approach includes fine-tuning a LLaMA 2 base model for answer extraction (AE) and question generation (QG). We evaluate the resulting system using common automated metrics and a manual evaluation. We find that our system is comparable to the latest research and meets our objectives.
Recommended Citation
Hybl, Matous, "Comprehensive Question and Answer Generation with LLaMA 2" (2024). MS in Computer Science Theses. 2.
https://knowledge.e.southern.edu/mscs_theses/2